Understanding service uncertainties in industrial product–service system cost estimation

Erkoyuncu, John Ahmet; Roy, Rajkumar; Shehab, Essam; Cheruvu, Kalyan S.

doi:10.1007/s00170-010-2767-3

Cited by 126 publications

(64 citation statements)

References 73 publications

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“…The purpose of a PSS may be shared by a diverse network of stakeholders undertaking a complex offset of interdependent activities within the virtual boundaries defined by the concept of enterprise (Purchase et al, 2011). Identifying the service-delivering activities and their linkages is necessary in order to adequately address service uncertainty (Erkoyuncu et al, 2011b).…”

Section: Challenge 2: What Is the Purpose Of Costing An Advanced Servmentioning

confidence: 99%

“…Non-probabilistic approaches such as possibility and subjective probability theory can address fuzziness and other, nonspecific ambiguities. However, most of the identified sources of uncertainty in delivering such services as assets' availability have aleatory nature (Erkoyuncu et al, 2011b).…”

Section: Challenge 3: What Are the Computational Aspects Of Costing Amentioning

confidence: 99%

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A through-life costing methodology for use in product–service-systems

Settanni

Newnes

Thenent

et al. 2014

International Journal of Production Economics

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Section: Challenge 2: What Is the Purpose Of Costing An Advanced Servmentioning

confidence: 99%

Section: Challenge 3: What Are the Computational Aspects Of Costing Amentioning

confidence: 99%

A through-life costing methodology for use in product–service-systems

Settanni

Newnes

Thenent

et al. 2014

International Journal of Production Economics

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“…It is quite another thing if you order something about which you are not really very clear". Theory seems to corroborate such findings by recognizing the existence of a so called "service uncertainty" concerning uncertainty cause by lack of "quality of information flow and knowledge" (Erkoyuncu, Roy, Shehab, & Cheruvu, 2011, p. 1223. Such statements bring evidences that clients are not always clear about what should be hired since the product of the service to be delivered is uncertain.…”

Section: Change In Services: Building a Definitionmentioning

confidence: 94%

Service Providers’ Willingness to Change as Innovation Inductor in Services: Validating a Scale

Moreira

Guimarães

Philippe

2016

BAR, Braz. Adm. Rev.

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This study explores the willingness of service providers to incorporate changes suggested by clients altering previously planned services during its delivery, hereby named Willingness to Change in Services [WCS]. We apply qualitative research techniques to map seven dimensions related to this phenomenon: Client relationship management; Organizational conditions for change; Software characteristics and development; Conditions affecting teams; Administrative procedures and decision-making conditions; Entrepreneurial behavior; Interaction with supporting organizations. These dimensions have been converted into variables composing a WCS scale later submitted to theoretical and semantic validations. A scale with 26 variables resulted from such procedures was applied on a large survey carried out with 351 typical Brazilian software development service companies operating all over the country. Data from our sample have been submitted to multivariate statistical analysis to provide validation for the scale. After factorial analysis procedures, 24 items have been validated and assigned to three factors representative of WCS: Organizational Routines and Values -12 variables; Organizational Structure for Change -6 variables; and Service Specificities -6 variables. As future contributions, we expect to see further testing for the WCS scale on alternative service activities to provide evidence about its limits and contributions to general service innovation theory.

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“…Co-creation is the ratio between the number of involved service activities and the number of service activities performed by the customer. Compare also (2) where the first term is used to calculate C i .…”

Section: Co-creation and Customer Factorsmentioning

confidence: 99%

“…Examples of customer factors include information, knowledge, experience, and commitment that customers bring in during the cocreation. For a provider, customer factors are a source of uncertainty since they affect service performance and service costs [2]. To reduce the gap between forecasted and real service costs, the modelling and understanding of customer factors and their impact on costs is fundamental.…”

Section: Introductionmentioning

confidence: 99%

Service System Analytics: Cost Prediction

Seiringer

Cardoso

Bischhoffshausen

2013

IFIP Advances in Information and Communication Technology

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Abstract. Services become every day more important for society. Cost prediction is one important aspect which has not received the required attention. Nonetheless, its impact on the economic success of service-based industries is considerable and, so, it cannot be overlooked. Therefore, in this paper we tackle the problem of cost prediction of service systems. Since previous work generally followed an ad hoc approach, we present a three layered approach based on customer factors to measure customer involvement since it is a good predictor for service cost. Service co-creation between customer and provider is the central concept of our costing approach. For service modelling we use Linked USDL, and to reason on costing data we use methods from service analytics. On the one hand, we reduce the uncertainty introduced by customers and can predict more accurate service costs. On the other hand, the systematic approach enables a better understanding of the costing problem and the service systems under study, and increases reusability of service analytics algorithms.

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Understanding service uncertainties in industrial product–service system cost estimation

Cited by 126 publications

References 73 publications

A through-life costing methodology for use in product–service-systems

A through-life costing methodology for use in product–service-systems

Service Providers’ Willingness to Change as Innovation Inductor in Services: Validating a Scale

Service System Analytics: Cost Prediction

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